The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning. Learn more →
Hydra Alternatives
Similar projects and alternatives to hydra
-
WorkOS
The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
-
InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
-
hydra
Hydra: Column-oriented Postgres. Add scalable analytics to your project in minutes. (by hydradatabase)
-
lightning-hydra-template
PyTorch Lightning + Hydra. A very user-friendly template for ML experimentation. ⚡🔥⚡
-
yamlpath
YAML/JSON/EYAML/Compatible get/set/merge/validate/scan/convert/diff processors using powerful, intuitive, command-line friendly syntax.
-
python-dotenv
Reads key-value pairs from a .env file and can set them as environment variables. It helps in developing applications following the 12-factor principles.
-
SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
hydra reviews and mentions
- Hydra – a Framework for configuring complex applications
-
Show HN: Hydra - Open-Source Columnar Postgres
Nice tool, only unfortunate name, consider changing it. Already very well know security tool named hydra https://github.com/vanhauser-thc/thc-hydra been around since 2001. Then facebook went ahead and named their config tool hydra https://github.com/facebookresearch/hydra on top of it. Like we get it, hydra popular mythology but we could use more original naming for tools
-
Show HN: Hydra 1.0 – open-source column-oriented Postgres
This looks really impressive, and I'm excited to see how it performs on our data!
P.S., I think the name conflicts with Hydra, the configuration management library: https://hydra.cc/
-
Best practice for saving logits/activation values of model in PyTorch Lightning
I've been trying to learn PyTorch Lightning and Hydra in order to use/create my own custom deep learning template (e.g. like this) as it would greatly help with my research workflow. A lot of the work I do requires me to analyse metrics based on the logits/activations of the model.
-
[D] Alternatives to fb Hydra?
However, hydra seems to have several limitations that are really annoying and are making me reconsider my choice. Most problematic is the inability to group parameters together in a multirun. Hydra only supports trying all combinations of parameters, as described in https://github.com/facebookresearch/hydra/issues/1258, which does not seem to be a priority for hydra. Furthermore, hydras optuna optimizer implementation does not allow for early pruning of bad runs, which while not a deal breaker is definitely a nice to have feature.
-
Show HN: Lightweight YAML Config CLI for Deep Learning Projects
Do you hate the fact that they don't let you return the config file: https://github.com/facebookresearch/hydra/issues/407
-
Config management for deep learning
I kind of built this due to frustrations with Hydra. Hydra is an end to end framework, it locks you into a certain DL project format, it decides logging, model saving and a whole host of things. For example Hydra can do the same config file overwriting that I allow but you have to store the config file with the name config.yaml inside a specific folder. On top of that hydra doesn’t let you return the config file from the main function so you have to put all the major logic in the main function itself (link), the authors claim this is by design. I can find Hydra useful for a mature less experimental project. But in my robotics and ML research, I like being able to write code where I want and integrating it how I want, especially when debugging for which I think this package is useful. TLDR; If you just want the config file functionality use my package, if you want a complete DL project manager use Hydra. While hydra implements this config file functionality, it also adds a lot of restrictions to project structure that you might not like.
-
The YAML Document from Hell
For managing configs of ML experiments (where each experiment can override a base config, and "variant" configs can further override the experiment config, etc), Hydra + Yaml + OmegaConf is really nice.
https://hydra.cc/
I admit I don't fully understand all the advanced options in Hydra, but the basic usage is already very useful. A nice guide is here:
https://florianwilhelm.info/2022/01/configuration_via_yaml_a...
- Hydra - namestitev in osnovna uporaba
- Hydra - namestitevt in osnovna uporaba
-
A note from our sponsor - WorkOS
workos.com | 24 Apr 2024
Stats
facebookresearch/hydra is an open source project licensed under MIT License which is an OSI approved license.
The primary programming language of hydra is Python.
Sponsored